1. Technical Field
Embodiments of the present invention relate generally to techniques for processing decoded video data and, more particularly, to techniques for generating and adding random noise to mask visual compression artifacts in decoded video data.
2. Description of the Related Art
This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present invention, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present invention. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
As the popularity of mobile and portable electronic devices continues to grow, the demand for network-based digital multimedia has also increased. For example, many portable electronic devices, such as cellular phones and portable media players, are now capable of wirelessly connecting to and communicating through the Internet or through other networks, such as local or wide area networks, allowing a user to download or stream multimedia. However, transfer rates for downloading or streaming media are typically limited by the maximum bandwidth of a particular network, and may be further limited by any other additional network traffic simultaneously occurring on the particular network (e.g., concurrent downloads and transfers by other users).
To provide an example, it is not uncommon for video data having a window size of 320×240 pixels and a frame rate of 15 frames per second (fps) to be encoded at a bit rate of 300 kilobits/second (kb/s). At this bit rate, approximately 128.7 megabytes (MB) is required to represent one hour of video data. Thus, to stream the 128.7 MB of video data in real time, a network must support a consistent bandwidth of at least 300 kb/s, which may be well above the capabilities of some wireless or local networks. Alternatively, if a user decides to download and store a copy of the video data locally on a device, or to temporarily store the video data in memory (e.g., caching or buffering) for playback, the transfer rate for the download is still limited by the maximum network bandwidth. As such, the user may have to wait an excessive length of time for a download to complete before being able to view the video data. Moreover, mobile and portable electronic devices may be limited by the amount of storage space or memory available. Accordingly, downloading and/or storing local copies of very large video files may be impractical for some mobile or portable electronic devices.
One method for overcoming the aforementioned drawbacks of streaming media is through video compression, which refers generally to techniques for reducing the quantity of video data used to represent video images, while retaining as much of the original video image quality as possible. By compressing video data prior to transmission across a network and subsequently decoding the compressed video data on the receiving mobile or portable device, the total amount of video data transferred is reduced, thereby reducing the bit rate and the bandwidth required to transmit the digital video. For example, one such video compression standard, H.264 (also known as MPEG-4 Part 10) provides a high video compression algorithm capable of maintaining a high quality image while compressing video data by a factor of more than 30 times.
Disadvantageously, most video compression standards use lossy data compression techniques in which data determined by a particular compression algorithm to be of lesser importance to the overall content, but which is nonetheless discernible and objectionable to the user, is discarded. As a result, certain video compression algorithms may introduce visual artifacts into the decoded video stream, which may be distracting to a user when viewing the decoded video data. Such visual artifacts are generally attributable to the latent error in lossy data compression and may appear more frequently as higher video compression rates are used. Moreover, such artifacts are exacerbated when the decoded video images are scaled to larger high definition displays.
One solution for reducing the impact of visual artifacts is by introducing random noise into the video stream after the compressed video is decoded. This technique is often referred to as “random dithering.” Although the added noise does not eliminate the visual artifacts, it may reduce the ability of the user to perceive the artifacts, thus rendering them less distracting to the human eye.